{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fa631910",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from numpy import genfromtxt\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "df9b06aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100,)\n",
      "[32.50234527 53.42680403 61.53035803 47.47563963 59.81320787 55.14218841\n",
      " 52.21179669 39.29956669 48.10504169 52.55001444 45.41973014 54.35163488\n",
      " 44.1640495  58.16847072 56.72720806 48.95588857 44.68719623 60.29732685\n",
      " 45.61864377 38.81681754 66.18981661 65.41605175 47.48120861 41.57564262\n",
      " 51.84518691 59.37082201 57.31000344 63.61556125 46.73761941 50.55676015\n",
      " 52.22399609 35.56783005 42.43647694 58.16454011 57.50444762 45.44053073\n",
      " 61.89622268 33.09383174 36.43600951 37.67565486 44.55560838 43.31828263\n",
      " 50.07314563 43.87061265 62.99748075 32.66904376 40.16689901 53.57507753\n",
      " 33.86421497 64.70713867 38.11982403 44.50253806 40.59953838 41.72067636\n",
      " 51.08863468 55.0780959  41.37772653 62.49469743 49.20388754 41.10268519\n",
      " 41.18201611 50.18638949 52.37844622 50.13548549 33.64470601 39.55790122\n",
      " 56.13038882 57.36205213 60.26921439 35.67809389 31.588117   53.66093226\n",
      " 46.68222865 43.10782022 70.34607562 44.49285588 57.5045333  36.93007661\n",
      " 55.80573336 38.95476907 56.9012147  56.86890066 34.3331247  59.04974121\n",
      " 57.78822399 54.28232871 51.0887199  50.28283635 44.21174175 38.00548801\n",
      " 32.94047994 53.69163957 68.76573427 46.2309665  68.31936082 50.03017434\n",
      " 49.23976534 50.03957594 48.14985889 25.12848465]\n",
      "(100,)\n",
      "[ 31.70700585  68.77759598  62.5623823   71.54663223  87.23092513\n",
      "  78.21151827  79.64197305  59.17148932  75.3312423   71.30087989\n",
      "  55.16567715  82.47884676  62.00892325  75.39287043  81.43619216\n",
      "  60.72360244  82.89250373  97.37989686  48.84715332  56.87721319\n",
      "  83.87856466 118.5912173   57.25181946  51.39174408  75.38065167\n",
      "  74.76556403  95.45505292  95.22936602  79.05240617  83.43207142\n",
      "  63.35879032  41.4128853   76.61734128  96.76956643  74.08413012\n",
      "  66.58814441  77.76848242  50.71958891  62.12457082  60.81024665\n",
      "  52.68298337  58.56982472  82.90598149  61.4247098  115.2441528\n",
      "  45.57058882  54.0840548   87.99445276  52.72549438  93.57611869\n",
      "  80.16627545  65.10171157  65.56230126  65.28088692  73.43464155\n",
      "  71.13972786  79.10282968  86.52053844  84.74269781  59.35885025\n",
      "  61.68403752  69.84760416  86.09829121  59.10883927  69.89968164\n",
      "  44.86249071  85.49806778  95.53668685  70.25193442  52.72173496\n",
      "  50.39267014  63.64239878  72.24725107  57.81251298 104.25710159\n",
      "  86.64202032  91.486778    55.23166089  79.55043668  44.84712424\n",
      "  80.20752314  83.14274979  55.72348926  77.63418251  99.05141484\n",
      "  79.12064627  69.58889785  69.51050331  73.68756432  61.36690454\n",
      "  67.17065577  85.66820315 114.85387123  90.12357207  97.91982104\n",
      "  81.53699078  72.11183247  85.23200734  66.22495789  53.45439421]\n"
     ]
    }
   ],
   "source": [
    "# 载入数据\n",
    "data = np.genfromtxt(\"data.csv\",delimiter=\",\")\n",
    "x_data = data[:,0,np.newaxis]\n",
    "y_data = data[:,1,np.newaxis]\n",
    "# x_data = data[:,0]\n",
    "# y_data = data[:,1]\n",
    "plt.scatter(x_data,y_data)\n",
    "plt.show()\n",
    "print(x_data.shape)\n",
    "print(x_data)\n",
    "print(y_data.shape)\n",
    "print(y_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "072b2fc9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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